Magnetic Resonance Imaging (MRI) can generate cross-sectional images in any plane (including oblique planes). Medical MRI most frequently relies on the relaxation properties of excited hydrogen nuclei (protons) in water and fat. When the object to be imaged is placed in a powerful, uniform magnetic field the spins of the atomic nuclei with non-integer spin numbers within the tissue all align either parallel to the magnetic field or anti-parallel. The output result of an MRI scan is an MRI contrast image or a series of MRI contrast images.
In order to understand MRI contrast, it is important to have some understanding of the time constants involved in relaxation processes that establish equilibrium following RF excitation. As the excited protons relax and realign, they emit energy at rates which are recorded to provide information about their environment. The realignment of proton spins with the magnetic field is termed longitudinal relaxation and the time (typically about 1 sec) required for a certain percentage of the tissue nuclei to realign is termed “Time 1” or T1. T2-weighted imaging relies upon local dephasing of spins following the application of the transverse energy pulse; the transverse relaxation time (typically <100 ms for tissue) is termed “Time 2” or T2. These relaxation times are also expressed as relaxation rates R1 (=1/T1) and R2 (=1/T2). The total signal depends on the number of protons, or proton density PD. On the scanner console all available parameters, such as echo time TE, repetition time TR, flip angle α and the application of preparation pulses (and many more), are set to certain values. Each specific set of parameters generates a particular signal intensity in the resulting images depending on the characteristics of the measured tissue.
Further, many neurological diseases, such as Alzheimer's disease and multiple sclerosis (MS), lead to brain atrophy, i.e., a loss of brain tissue volume in a faster rate than normal. It is important to monitor the brain volume evolution of these patients having such diseases to determine the severity of the disease and the impact of treatment. Generally the brain volume is normalized with the intracranial volume to minimize the effect of head size or incomplete acquisition coverage with the imaging modality. The ratio of the brain parenchymal volume (BPV) and the intracranial volume (ICV) is called the brain parenchymal fraction (BPF) and is considered a measure for brain atrophy (see, e.g., Grassiot B, et al. Quantification and clinical relevance of brain atrophy in multiple sclerosis: a review, J Neurol 2009; 256:1397-1412). To obtain the BPF manually is very time consuming and imprecise.
Further, U.S. Pat. No. 6,366,797 describes a method based on structure recognition and image thresholding in MR images. U.S. Pat. No. 5,262,945 describes a method that uses image intensity histograms of MR images, curve fitting and thresholding. These methods generate object recognition directly from MR images and hence require ad-hoc filtering and empirical image intensity thresholding. This is a challenge since any change in MR scanner settings or any unexpected imperfection in the acquisition changes the image intensity. Therefore the filtering and thresholding must be re-optimized for each MR image leading to an uncertain result.
It would therefore be desirable to provide improved methods and devises for obtaining clinical brain measures such as the brain parenchymal volume (BPV), the intracranial volume (ICV) and the brain parenchymal fraction (BPF).